Linear mixed-effect models for correlated response to process electroencephalogram recordings.

Autor: Meinardi VB; I.A.P Ciencias Humanas, Universidad Nacional de Villa María, Arturo Jauretche 1555, 5900 Villa María, Córdoba, Argentina.; Centro de Investigación y Transferencia. UNVM, Arturo Jauretche 1555, 5900 Córdoba, Argentina., López JMD; Instituto Argentino de Ciencias de la Conducta (IACCo), Entre Ríos 419, 5000 Córdoba, Argentina.; Facultad de Matemática, Física, Astronomía y Computación, Universidad Nacional de Córdoba. Haya de la Torre y Medina Allende, Ciudad Universitaria, 5000 Córdoba, Argentina.; Facultad de Ciencias Químicas, Universidad Nacional de Córdoba. Haya de la Torre y Medina Allende, Ciudad Universitaria, 5000 Córdoba, Argentina., Fajreldines HD; Departamento de Investigaciones Biomédicas, Instituto Privado de Neurociencias. Felix, Fríaz 129, 5000 Córdoba, Argentina.; Facultad de Ciencias Químicas, Universidad Nacional de Córdoba. Haya de la Torre y Medina Allende, Ciudad Universitaria, 5000 Córdoba, Argentina., Boyallian C; Centro de Investigación y Estudios de Matemática. Famaf, UNC., Haya de la Torre y Medina Allende, Ciudad Universitaria, 5000 Córdoba, Argentina.; Facultad de Matemática, Física, Astronomía y Computación, Universidad Nacional de Córdoba. Haya de la Torre y Medina Allende, Ciudad Universitaria, 5000 Córdoba, Argentina., Balzarini M; Estadística y Biometría, Universidad Nacional de Córdoba, UFYMA INTA-CONICET. Camino 60 cuadras km 5 1/2 s/n, 5020 Córdoba, Argentina.
Jazyk: angličtina
Zdroj: Cognitive neurodynamics [Cogn Neurodyn] 2024 Jun; Vol. 18 (3), pp. 1197-1207. Date of Electronic Publication: 2023 Jun 19.
DOI: 10.1007/s11571-023-09984-6
Abstrakt: A data set of clinical studies of electroencephalogram recordings (EEG) following data acquisition protocols in control individuals (Eyes Closed Wakefulness - Eyes Open Wakefulness, Hyperventilation, and Optostimulation) are quantified with information theory metrics, namely permutation Shanon entropy and permutation Lempel Ziv complexity, to identify functional changes. This work implement Linear mixed-effects models (LMEMs) for confirmatory hypothesis testing. The results show that EEGs have high variability for both metrics and there is a positive correlation between them. The mean of permutation Lempel-Ziv complexity and permutation Shanon entropy used simultaneously for each of the four states are distinguishable from each other. However, used separately, the differences between permutation Lempel-Ziv complexity or permutation Shanon entropy of some states were not statistically significant. This shows that the joint use of both metrics provides more information than the separate use of each of them. Despite their wide use in medicine, LMEMs have not been commonly applied to simultaneously model metrics that quantify EEG signals. Modeling EEGs using a model that characterizes more than one response variable and their possible correlations represents a new way of analyzing EEG data in neuroscience.
Competing Interests: Conflict of interestThe authors declare no conflict of interest.
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Databáze: MEDLINE
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